Korean Journal of Agricultural Science (농업과학연구)

Institute of Agricultural Science, CNU (충남대학교 농업과학연구소)
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Noncontact measurements of the morphological phenotypes of sorghum using 3D LiDAR point cloud

  • Eun-Sung, Park (Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University) ;
  • Ajay Patel, Kumar (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) ;
  • Muhammad Akbar Andi, Arief (Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University) ;
  • Rahul, Joshi (Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University) ;
  • Hongseok, Lee (National Institute of Crop Science, Rural Development Administration) ;
  • Byoung-Kwan, Cho (Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University)
  • Received : 2022.06.10
  • Accepted : 2022.07.13
  • Published : 2022.09.01
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Abstract

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R2 of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

Keywords

Acknowledgement

본 연구는 농촌진흥청(Rural Development Administration) 공동연구사업(과제번호: PJ015689)의 지원을 받아 이루어진 것임.

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